Gábor Nagypál

A Fuzzy Model for Representing Uncertain, Subjective, and Vague Temporal Knowledge in Ontologies

Time modeling is a crucial feature in many application domains. However, temporal information often is not crisp, but is uncertain, subjective and vague. This is particularly true when representing historical information, as historical accounts are inherently imprecise. Similarly, we conjecture that in the Semantic Web representing uncertain temporal information will be a common requirement. Hence, existing approaches for temporal modeling based on crisp representation of time cannot be applied to these advanced modeling tasks. To overcome these difficulties, in this paper we present fuzzy interval-based temporal model capable of representing imprecise temporal knowledge. Our approach naturally subsumes existing crisp temporal models, i.e. crisp temporal relationships are intuitively represented in our system. Apart from presenting the fuzzy temporal model, we discuss how this model is integrated with the ontology model to allow annotating ontology definitions with time specifications.

Improving information retrieval effectiveness by using domain knowledge stored in ontologies

The huge number of available documents on the Web makes finding relevant ones a challenging task. The quality of results that traditional full-text search engines provide is still not optimal for many types of user queries. Especially the vagueness of natural languages, abstract concepts, semantic relations and temporal issues are handled inadequately by full-text search. Ontologies and semantic metadata can provide a solution for these problems. This work examines how ontologies can be optimally exploited during the information retrieval process, and proposes a general framework which is based on ontology-supported semantic metadata generation and ontology-based query expansion. The framework can handle imperfect ontologies and metadata by combining results of simple heuristics, instead of relying on a “perfect” ontology. This allows integrating results from traditional full-text engines, and thus supports a gradual transition from classical full-text search engines to ontology-based ones.

ImageNotion: methodology, tool support and evaluation

The content of image archives changes rapidly. This makes the traditional separation of ontology development and image annotation steps no longer feasible. In this paper, we present an approach, termed ImageNotion that allows for the collaborative development of domain ontologies directly by domain experts with minimal ontology experience. ImageNotion is both a methodology based on the idea of the ontology maturing process model, and the name of the tool supporting this methodology. ImageNotion embeds the creation of ontology entities, termed imagenotions, into the work process of creating semantic annotations of images and their parts. Both the creation of imagenotions and the creation of image annotations are visual, user friendly processes, implemented by a web application that integrates all of the required functionality in one consistent framework. Besides the theoretical concepts, this paper also presents the results of our evaluation of the system with experienced image annotators and librarians having minimal ontology background.

A Reasoning Framework for Rule-Based WSML

WSML is an ontology language specifically tailored to annotate Web Services, and part of its semantics adheres to the rule-based knowledge representation paradigm of logic programming. We present a framework to support reasoning with rule-based WSML language variants based on existing Datalog inference engines. Therein, the WSML reasoning tasks of knowledge base satisfiability and instance retrieval are implemented through a language mapping to Datalog rules and Datalog querying. Part of the WSML semantics is realized by a fixed set of rules that form meta-level axioms. Furthermore, the framework exhibits some debugging functionality that allows for identifying violated constraints and for pointing out involved instances and problem types. Its highly modular architecture facilitates easy extensibility towards other language variants and additional features. The available implementation of the framework provides the first reasoners for the WSML language.

The combination of techniques for automatic semantic image annotation generation in the IMAGINATION application

The IMAGINATION project provides image-based navigation for digital cultural and scientific resources. Users can click on parts of an image to find other, interesting images to a given context. In this paper, we present the core parts of the IMAGINATION application. To allow the navigation through images, this application automatically generates high quality semantic metadata. Therefore it combines automated processes for person and object detection, face detection and identification in images together with text mining techniques that exploit domain specific ontologies.

Intelligent Retrieval of Digital Resources by Exploiting Their Semantic Context

Although the first digital archives storing a huge number of resources came into existence years ago, they still lack effective retrieval methods. The most obvious example is the World Wide Web: search engines are improved constantly, however, their hits are still unsatisfactory apart from simplest queries. Most prosperous solutions employ user contexts to estimate the user’s information demand and use this information to deliver more adequate results. In the current paper we introduce the idea of resource context-based information retrieval. In this approach, semantic context description is assigned to each digital resource known to the system and this semantic metadata are exploited by each step during an intelligent search process. Our solution is implemented and evaluated in the VICODI project, as part of a web portal for European history.

Evaluation of the Navigation through Image Parts in the ImageNotion Application

In our work on the ImageNotion methodology and tools, we apply semantic technologies on image archives. In this paper, we show evaluation results on our work on the user interface for semantic image search and expected navigation through image parts. We conducted an online survey with more than hundred participants. A unique feature of our evaluation is that our evaluators filled the survey based on a concrete, working semantic application, i.e., based on the publicly available online version of our system.